Successful wind power projects start with a realistic representation of the surface, more specifically the surface roughness of the site. This thesis investigates the use of airborne laser scans to model the surface roughness around a new wind farm. Estimations are made to find out how forest management and tree growth affects roughness length and displacement height. Data from scans two years apart for a specific site is provided by the Swedish governmental land registration authority. Next, tree height and plant area index methods are applied and analyzed using MATLAB. The results shows a difference of roughness length between 10.34% and 36.21% during an eight year period. WindPRO/WAsP is used to import roughness lengths for four specific cases. Height contour lines and meteorological data is taken from a long term corrected MESO data set. The results indicate a reduction in uncertainty in annual energy production between 0.79% and 2.89% across four different cases. This effect becomes significantly larger (12.76%) when comparing with classical land cover maps. Further on, effects of turbulence intensity are simulated.Finally, the results of a survey, sent to three large forest land owners in Sweden, show there is an interest in adapting forest management plans in favor of wind energy production if benefits can be shared.

This thesis introduces a design optimization methodology that is based on minimizing the Cost of Energy (COE) of a Horizontal Axis Wind Turbine (HAWT) that is to be operated at a specific wind site. In the design methodology for the calculation of the Cost of Energy, the Annual Energy Production (AEP) model to calculate the total energy generated by a unit wind turbine throughout a year and the total cost of that turbine are used. The AEP is calculated using the Blade Element Momentum (BEM) theory for wind turbine power and the Weibull distribution for the wind speed characteristics of selected wind sites. For the blade profile sections, either the S809 airfoil profile for all spanwise locations is used or NREL S-series airfoil families, which have different airfoil profiles for different spanwise sections, are used,. Lift and drag coefficients of these airfoils are obtained by performing computational fluid dynamics analyses. In sample design optimization studies, three different wind sites that have different wind speed characteristics are selected. Three scenarios are generated to present the effect of the airfoil shape as well as the turbine power. For each scenario, design optimizations of the reference wind turbines for the selected wind sites are performed the Cost of Energy and Annual Energy Production values are compared.

Le développement de la production d'énergie éolienne nécessite des méthodes précises et bien établies pour l'évaluation de la ressource éolienne, étape essentielle dans la phase avant-projet d'une future ferme. Au cours de ces deux dernières décennies, les modèles d'écoulements linéaires ont été largement utilisés dans l'industrie éolienne pour l'évaluation de la ressource et pour la définition de la disposition des turbines. Cependant, les incertitudes des modèles linéaires dans la prévision de la vitesse du vent sur terrain complexe sont bien connues. Elles conduisent à l'utilisation de modèles CFD, capables de modéliser les écoulements complexes de manière précise autour de caractéristiques géographiques spécifiques. Les modèles méso-échelle peuvent prédire le régime de vent à des résolutions de plusieurs kilomètres mais ne sont pas bien adaptés pour résoudre les échelles spatiales inférieures à quelques centaines de mètres. Les modèles de CFD peuvent capter les détails des écoulements atmosphériques à plus petite échelle, mais nécessitent de documenter précisément les conditions aux limites. Ainsi, le couplage entre un modèle méso-échelle et un modèle CFD doit permettre d'améliorer la modélisation fine de l'écoulement pour les applications dans le domaine de l'énergie éolienne en comparaison avec les approches opérationnelles actuelles. Une campagne de mesure d'un an a été réalisée sur un terrain complexe dans le sud de la France durant la période 2007-2008. Elle a permis de fournir une base de données bien documentée à la fois pour les paramètres d'entrée et les données de validation. La nouvelle méthodologie proposée vise notamment à répondre à deux problématiques: le couplage entre le modèle méso-échelle et le modèle CFD en prenant en compte une forte variation spatiale de la topographie sur les bords du domaine de simulation, et les erreurs de prédiction du modèle méso-échelle. Le travail réalisé ici a consisté à optimiser le calcul du vent sur chaque face d'entrée du modèle CFD à partir des valeurs issues des verticales du modèle de méso-échelle, puis à mettre en œuvre une assimilation de données basée sur la relaxation newtonienne (nudging). La chaîne de modèles considérée ici est composée du modèle de prévision de Météo-France ALADIN et du code de CFD open-source Code_Saturne. Le potentiel éolien est ensuite calculé en utilisant une méthode de clustering, permettant de regrouper les conditions météorologiques similaires et ainsi réduire le nombre de simulations CFD nécessaires pour reproduire un an (ou plus) d'écoulement atmosphérique sur le site considéré. La procédure d'assimilation est réalisée avec des mesures issues d'anémomètre à coupelles ou soniques. Une analyse détaillée des simulations avec imbrication et avec ou sans assimilation de données est d'abord présentée pour les deux directions de vent dominantes, avec en particulier une étude de sensibilité aux paramètres intervenant dans l'imbrication et dans l'assimilation. La dernière partie du travail est consacrée au calcul du potentiel éolien en utilisant une méthode de clustering. La vitesse annuelle moyenne du vent est calculée avec et sans assimilation, puis est comparée avec les mesures non assimilées et les résultats du modèle WAsP. L'amélioration apportée par l'assimilation de données sur la distribution des écarts avec les mesures est ainsi quantifiée pour différentes configurations / The development of wind energy generation requires precise and well-established methods for wind resource assessment, which is the initial step in every wind farm project. During the last two decades linear flow models were widely used in the wind industry for wind resource assessment and micro-siting. But the linear models inaccuracies in predicting the wind speeds in very complex terrain are well known and led to use of CFD, capable of modeling the complex flow in details around specific geographic features. Mesoscale models (NWP) are able to predict the wind regime at resolutions of several kilometers, but are not well suited to resolve the wind speed and turbulence induced by the topography features on the scale of a few hundred meters. CFD has proven successful in capturing flow details at smaller scales, but needs an accurate specification of the inlet conditions. Thus coupling NWP and CFD models is a better modeling approach for wind energy applications. A one-year field measurement campaign carried out in a complex terrain in southern France during 2007-2008 provides a well documented data set both for input and validation data. The proposed new methodology aims to address two problems: the high spatial variation of the topography on the domain lateral boundaries, and the prediction errors of the mesoscale model. It is applied in this work using the open source CFD code Code_Saturne, coupled with the mesoscale forecast model of Météo-France (ALADIN). The improvement is obtained by combining the mesoscale data as inlet condition and field measurement data assimilation into the CFD model. Newtonian relaxation (nudging) data assimilation technique is used to incorporate the measurement data into the CFD simulations. The methodology to reconstruct long term averages uses a clustering process to group the similar meteorological conditions and to reduce the number of CFD simulations needed to reproduce 1 year of atmospheric flow over the site. The assimilation procedure is carried out with either sonic or cup anemometers measurements. First a detailed analysis of the results obtained with the mesoscale-CFD coupling and with or without data assimilation is shown for two main wind directions, including a sensitivity study to the parameters involved in the coupling and in the nudging. The last part of the work is devoted to the estimate of the wind potential using clustering. A comparison of the annual mean wind speed with measurements that do not enter the assimilation process and with the WAsP model is presented. The improvement provided by the data assimilation on the distribution of differences with measurements is shown on the wind speed and direction for different configurations

The recent worldwide economic crisis, climate change and global warming have emphasized that the need for low carbon emissions while also ensuring the economic feasibility. In this paper, wind power potential of ETD in KTH was investigated. The technical and economical feasibility of tower mounted small scale standalone wind turbine installation is conducted. The potential of wind power production was statistically analysed. The average wind speed data of four-season interval of one year period (2011) which its measurement was taken on the roof top of the ETDB, and this was adopted and analysed in order to find out the potential of wind power generation. The Rayleigh distribution probability was applied to calculate the wind speed distribution at KTH, by doing so the annual wind power potential at the area and annual energy production of the chosen wind turbine was estimated, after the selection of a proper wind turbine have been made upon the site conditions. Therefore, the study result shows that installation of the wind turbine at 24 meters hub height for this particular area will have a better performance of annual energy production, capacity factor, carbon savings and better economical value than the current turbine installed at 17 meters height at the ETD. The economic evaluation shows that the turbine can save an electricity bill of US$3661.05 per year and cover 1.84% of the electricity consumption of the ETD by reducing its respective CO2 emission from the electricity use at the department. Moreover, the payback period of the turbine installation with the inclusion of the green certificate is approximately 14 years which is more feasible if it is considered for small wind turbines too, which is already in practice for renewables including wind power in Sweden.

The aim of this thesis is to evaluate different repowering alternatives from the viewpoint of increasing power production from existing offshore wind farms (OWF), as some of the first commissioned OWFs are approaching the end of their expected lifetime. The thesis presents a literature review of components and financial aspects that are of importance for repowering of OWFs. In the literature review, risks and uncertainties regarding repowering are also lifted and analysed. The thesis contains a case study on Horns Rev 1 OWF, where three different repowering scenarios are evaluated by technical and financial performance, aiming to compare the cost of repowering alternatives. The design of the case study is based around previous studies of offshore repowering having focused mainly on achieving the lowest possible levelized cost of energy (LCoE) and highest possible capacity factor, often resulting in suggested repowering utilizing smaller wind turbines than the existing ones. In order to evaluate the financial viability of repowering alternatives, the software RETScreen Expert was used to estimate the annual energy production (AEP) after losses and calculate the net present value (NPV) and LCoE for lifetime extension and full repowering utilizing different capacity wind turbines. Input values from the literature as well as real wind resource measurements from the site was utilized to achieve as accurate results as possible. The result of the case study shows that repowering of OWFs have the possibility of providing a very strong business case with all scenarios resulting in a positive NPV as well as lower LCoE than the benchmarked electricity production price. Although the initial investment cost of the different repowering alternatives presented in this thesis still are uncertain to some extent, due to the lack of reliable costs for repowering alternatives, this thesis provides a base for further research regarding the repowering of OWFs.

The wind power prediction plays a vital role in a wind power project both during the planning and operational phase of a project. A time series based wind power prediction model is introduced and the simulations are run for different case studies. The prediction model works based on the input from 1) nearby representative wind measuring station 2) Global average wind speed value from Meteorological Institute Uppsala University mesoscale model (MIUU) 3) Power curve of the wind turbine. The measured wind data is normalized to minimize the variation in the wind speed and multiplied with the MIUU to get a distributed wind speed. The distributed wind speed is then used to interpolate the wind power with the help of the power curve of the wind turbine. The interpolated wind power is then compared with the Actual Production Data (APD) to validate the prediction model. The simulation results show that the model works fairly predicting the Annual Energy Production (AEP) on monthly averages for all sites but the model could not follow the APD trend on all cases. The sensitivity analysis shows that the variation in production does not depend on ’the variation in roughness class’ nor ’the difference in distance between the measuring station and the wind farm’. The thesis has been concluded from the results that the model works fairly predicting the AEP for all cases within the variation bounds. The accuracy of the model has been validated only for monthly averages since the APD was available only on monthly averages. But the accuracy could be increased based on future work, to assess the Power law exponent (a) parameter for different terrain and validate the model for different time scales provided if the APD is available on different time scales.